Geographic Information Systems (GIS) are commonly employed to solve problems related to landfill siting and optimization of waste collection. This research aims to develop an easily implementable tool to optimize the topology of waste management regions in various Canadian jurisdictions using ArcGIS ModelBuilder. Landfill count, populated places, and road length are minimized using standard deviation to determine optimized tessellations. In Nova Scotia, reductions in standard deviation of 9.6e30.4% are observed between original and optimized tessellations. The results suggest that an optimized tessellation of Nova Scotia’s Federal subdivisions may perform better than that of their waste management regions. In Saskatchewan, reductions in standard deviation of 4.9e46.1% were observed between original and optimized tessellations. Considering all Saskatchewan Federal Subdivisions, no optimization occurred. However, partitions of Saskatchewan Federal Subdivisions yielded better results, with vertical partitions yielding a 30% decrease in standard deviation of roads, while landfills and population were reduced in the horizontal subdivision by 20.0% and 38.0%, respectively. This suggests that a different approach may be required for waste management regions in Northern Saskatchewan. Saskatchewan transportation planning committees regions had the highest standard deviation across all parameters, and optimized at the fourth iteration (landfills and populated places), and first iterations (roads), despite the fact that this tessellation was developed in direct relation to roads in the province. The proposed tool, however, showed a limited application in the City of Regina given that land use planning within City limits. This work will improve the data driven aspect of regional waste management system design.

Introduction & literature review

Waste collection and transportation constitutes a large fraction of total municipal solid waste management budgets worldwide (Chalkias and Lasaridi, 2009; Richter et al., 2018; Rathore and Sarmah, 2019). Waste collection and transportation cost of a given waste management system to a large degree depends on the distance between generation and disposal sites, and thus optimization of shape and size of a waste management region (WMR) is vital in reducing total operation cost. In Athens, Greece, costs for the collection and transportation of waste may account for more than 70% of total waste management costs (Chalkias and Lasaridi, 2009). In Bilaspur, India, collection and transportation account for 50e70% of total waste management costs (Rathore and Sarmah, 2019). Richter et al. (2018) found that Canadians spent about 46% of local waste management budgets on the collection and transportation of waste. Canadians have one of the highest waste generation rates in the world and send a majority of their waste to landfills for permanent disposal (Bruce et al., 2016; Wang et al., 2016; Richter et al., 2019). Despite the size of the country and its mediocre performance in waste diversion (Bruce et al., 2016; Wang et al., 2016; Pan et al., 2018), there is little published information on waste management systems in Canada (Lakhan, 2015; Zhu and Huang, 2017; Chowdhury et al., 2017; Richter et al., 2017, 2018). Fig. 1 shows the expenditure on collection and transportation at the local level in Nova Scotia (NS), Saskatchewan (SK), and Canada (CA). Nova Scotia is a leading Canadian province in waste diversion (Richter et al., 2017, 2018), whereas Saskatchewan ranks as at the bottom (Wang et al., 2016). Over time, there has been a steady increase in the cost of collection and transportation provincially and nationally.